Website:
benzcalder.com
Job details:
About the Role:
We are seeking a visionary Enterprise Architect specializing in Core Agentic AI and Autonomous Intelligent Ecosystems to lead the next-generation architecture for the SuperApp Marketplace.
This role moves beyond traditional banking rails to focus on building an autonomous intelligent layer powered by cutting-edge AI frameworks. You will lead the enterprise vision for multi-agent coordination, autonomous reasoning engines, LLM orchestration, and high-concurrency event-driven streaming across a hybrid GCP (Vertex AI) and Azure cloud ecosystem. If you are a pure-play AI Architect who excels at building self-learning agentic systems and scalable AI platforms at massive consumer scale, this role is for you.
Please note:
We are strictly looking for tech-first architects with deep hands-on expertise in Core Agentic AI, Generative AI, and Autonomous Systems. Profiles whose primary domain experience is limited to traditional legacy core banking, switch engines, or payment gateway platforms will not be considered.
Key Responsibilities & Deliverables:
- Agentic AI Reference Architecture: Design and deploy the foundational enterprise reference architecture for multi-agent autonomous systems, LLM orchestration, RAG pipelines, and vector databases.
- Autonomous Agent Ecosystems: Architect protocols for autonomous agent-to-agent communication, agentic workflows, memory persistence, and dynamic tool/API selection.
- Multi-Cloud AI Infrastructure: Build a resilient, low-latency multi-cloud integration framework connecting an Agentic AI Layer on GCP (Vertex AI, GKE) with cloud platform services on Azure.
- Event-Driven AI Streaming: Define streaming data patterns using Apache Kafka and Flink to pipe real-time transactional data into agentic decision engines.
- AI Safety & Zero-Trust Governance: Establish AI safety guardrails, continuous model observability, hallucination mitigation, IAM, and Zero-Trust security frameworks across autonomous agents.
- AI Product Metrics & Governance: Formulate technology scorecards tracking AI agent precision, recall, latency, bias/fairness metrics, and agentic task execution success rates.
Required Experience & Technical Expertise:
- 10–15 years of total experience in Enterprise Architecture, Distributed Systems, and scalable AI platform engineering.
- Deep specialization in Core Agentic AI, autonomous systems, or AI-first consumer tech/platform architectures.
- Proven track record building high-concurrency, high-scale consumer-facing digital applications.
Technical Skill Requirements:
- Agentic Frameworks & AI: Expertise in LangChain, LlamaIndex, AutoGen, CrewAI, Graph RAG, Vector Databases (Pinecone, Milvus, Qdrant), and Fine-tuning/RAG pipelines.
Cloud & AI Engines:
- GCP: Deep experience with Vertex AI, GKE, BigQuery, and Google Cloud AI infrastructure.
- Azure: Experience with Azure OpenAI services, AKS, and PaaS integrations.
- Architecture Patterns: Microservices, Domain-Driven Design (DDD), Event-Driven Streaming (Apache Kafka, Flink), CQRS, and open API standards.
- Language Stack: Python, Java, C++, or Go for low-latency AI orchestration layers.
Click on Apply to know more.